函数使得索引列失效

在索引列上使用函数使得索引失效的是常见的索引失效原因之一，因此尽可能的避免在索引列上使用函数。尽管可以使用基于函数的索引来
解决索引失效的问题，但如此一来带来的比如磁盘空间的占用以及列上过多的索引导致DML性能的下降。本文描述的是一个索引列上使用函数使
其失效的案例。

一、数据版本与原始语句及相关信息
  1.版本信息    

SQL> select * from v$version;

BANNER
----------------------------------------------------------------
Oracle Database 10g Release 10.2.0.3.0 - 64bit Production
PL/SQL Release 10.2.0.3.0 - Production
CORE    10.2.0.3.0      Production
TNS for Linux: Version 10.2.0.3.0 - Production
NLSRTL Version 10.2.0.3.0 - Production

  2.原始语句与其执行计划   

SQL> set autotrace traceonly exp;

SELECT acc_num,
       curr_cd,
       DECODE('20110728',
              (SELECT TO_CHAR(LAST_DAY(TO_DATE('20110728', 'YYYYMMDD')),
                              'YYYYMMDD')
               FROM   DUAL),
              0,
              adj_credit_int_lv1_amt + adj_credit_int_lv2_amt -
              adj_debit_int_lv1_amt - adj_debit_int_lv2_amt) AS interest
FROM   acc_pos_int_tbl ACC_POS_INT_TBL1
WHERE  SUBSTR(business_date, 1, 6) = SUBSTR('20110728', 1, 6)
       AND business_date <= '20110728';

Execution Plan
----------------------------------------------------------
Plan hash value: 3114115399

-------------------------------------------------------------------------------------
| Id  | Operation         | Name            | Rows  | Bytes | Cost (%CPU)| Time     |
-------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT  |                 |   336K|    12M| 96399   (1)| 00:19:17 |
|   1 |  FAST DUAL        |                 |     1 |       |     2   (0)| 00:00:01 |
|*  2 |  TABLE ACCESS FULL| ACC_POS_INT_TBL |   336K|    12M| 96399   (1)| 00:19:17 |
-------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - filter(SUBSTR("BUSINESS_DATE",1,6)='201107' AND
              "BUSINESS_DATE"<='20110728')

    从执行计划可以看出，SQL语句使用了全表扫描，而where 子句中只有唯一的一列business_date

  3.表上的索引信息     

SQL> set autotrace off;
SQL> set linesize 190
SQL> @Idx_Info
Enter value for owner: goex_admin
old  10:           AND owner = upper('&owner')
new  10:           AND owner = upper('goex_admin')
Enter value for table_name: ACC_POS_INT_TBL
old  11:           AND a.table_name = upper('&table_name')
new  11:           AND a.table_name = upper('ACC_POS_INT_TBL')

TABLE_NAME         INDEX_NAME               COL_NAM              CL_POS STATUS   IDX_TYP         DSCD
------------------ ------------------------ -------------------- ------ -------- --------------- ----
ACC_POS_INT_TBL    ACC_POS_INT_10DIG_IDX    SYS_NC00032$              1 VALID    FUNCTION-BASED  ASC
                                                                                 NORMAL

ACC_POS_INT_TBL    ACC_POS_INT_10DIG_IDX    BUSINESS_DATE             2 VALID    FUNCTION-BASED  ASC
                                                                                 NORMAL

ACC_POS_INT_TBL    ACC_POS_INT_10DIG_IDX    CURR_CD                   3 VALID    FUNCTION-BASED  ASC
                                                                                 NORMAL

ACC_POS_INT_TBL    PK_ACC_POS_INT_TBL       ACC_NUM                   1 VALID    NORMAL          ASC
ACC_POS_INT_TBL    PK_ACC_POS_INT_TBL       BUSINESS_DATE             2 VALID    NORMAL          ASC

    从索引的情况上来看有一个基于主键的索引包含了BUSINESS_DATE列，而查询语句并没有走索引而是选择的全表扫描，而且预估所返回
    的行Rows与bytes也是大的惊人，cost的值96399，接近10W。

二、分析与改造SQL语句
  1.原始的SQL语句分析
       SQL语句中where子句的business_date列实现对记录过滤
       business_date <= '20110728'条件不会限制索引的使用
       SUBSTR(business_date, 1, 6) = SUBSTR('20110728', 1, 6)使用了SUBSTR函数，限制了优化器选择索引
       基于business_date列来建立索引函数，从已存在的索引来看，必要性不大
   
  2.改造SQL语句
    SUBSTR(business_date, 1, 6) = SUBSTR('20110728', 1, 6)的实质是等于当月，即限制返回的行为从2011.7.1日至2011.7.28
    因此其返回的记录大于等于2011.7.1，且小于2011.7.28
    做如下改造
     business_date >=to_char(last_day(add_months(to_date('20110728','yyyymmdd'),-1)) + 1,'yyyymmdd')
   
  3.改造后的SQL语句   

SELECT acc_num,
       curr_cd,
       DECODE('20110728',
              (SELECT TO_CHAR(LAST_DAY(TO_DATE('20110728', 'YYYYMMDD')),
                              'YYYYMMDD')
               FROM   DUAL),
              0,
              adj_credit_int_lv1_amt + adj_credit_int_lv2_amt -
              adj_debit_int_lv1_amt - adj_debit_int_lv2_amt) AS interest
FROM   acc_pos_int_tbl ACC_POS_INT_TBL1
WHERE  business_date >=
       to_char(last_day(add_months(to_date('20110728', 'yyyymmdd'), -1)) + 1,
               'yyyymmdd')
       AND business_date <= '20110728';

   4.改造后的执行计划  

Execution Plan
----------------------------------------------------------
Plan hash value: 66267922

--------------------------------------------------------------------------------------------------
| Id  | Operation                   | Name               | Rows  | Bytes | Cost (%CPU)| Time     |
--------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT            |                    |  1065K|    39M| 75043   (1)| 00:15:01 |
|   1 |  FAST DUAL                  |                    |     1 |       |     2   (0)| 00:00:01 |
|   2 |  TABLE ACCESS BY INDEX ROWID| ACC_POS_INT_TBL    |  1065K|    39M| 75043   (1)| 00:15:01 |
|*  3 |   INDEX SKIP SCAN           | PK_ACC_POS_INT_TBL | 33730 |       | 41180   (1)| 00:08:15 |
--------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   3 - access("BUSINESS_DATE">='20110701' AND "BUSINESS_DATE"<='20110728')
       filter("BUSINESS_DATE">='20110701' AND "BUSINESS_DATE"<='20110728')

    改造后可以看到SQL语句的执行计划已经由原来的全表扫描改为执行INDEX SKIP SCAN，但其cost也并没有降低多少

三、进一步分析
  1.表的相关信息  

SQL> @Tab_Stat
Enter value for input_table_name: ACC_POS_INT_TBL
old  11: WHERE  table_name = upper('&input_table_name')
new  11: WHERE  table_name = upper('ACC_POS_INT_TBL')
Enter value for input_owner: goex_admin
old  12:           AND owner = upper('&input_owner')
new  12:           AND owner = upper('goex_admin')

  NUM_ROWS       BLKS    EM_BLKS  AVG_SPACE  CHAIN_CNT AVG_ROW_LEN AVG_ROWS_PER_BLOCK LST_ANLY  STA
---------- ---------- ---------- ---------- ---------- ----------- ------------------ --------- ---
  33659947     437206       1322        855          0          99                 77 27-SEP-11 NO

  2.索引的相关信息 

SQL> @Idx_Stat
Enter value for input_table_name: ACC_POS_INT_TBL
old  11: WHERE  table_name = upper('&input_table_name')
new  11: WHERE  table_name = upper('ACC_POS_INT_TBL')
Enter value for input_owner: goex_admin
old  12:           AND owner = upper('&input_owner')
new  12:           AND owner = upper('goex_admin')

BLEV IDX_NAME                          LF_BLKS   DST_KEYS   NUM_ROWS LF_PER_KEY DAT_BLK_PER_KEY   CLUS_FCT LST_ANLY
---- ------------------------------ ---------- ---------- ---------- ---------- --------------- ---------- ---------
   3 PK_ACC_POS_INT_TBL                 155658   33777720   33777720          1               1   33777447 27-SEP-11
   3 ACC_POS_INT_10DIG_IDX              160247   32850596   32850596          1               1   32763921 27-SEP-11

  3.尝试在BUSINESS_DATE列上创建索引   

SQL> create index I_ACC_POS_INT_TBL_BS_DT on ACC_POS_INT_TBL(BUSINESS_DATE) tablespace tbs_tmp nologging;

Index created.

SQL> @Idx_Stat
Enter value for input_table_name: ACC_POS_INT_TBL
old  11: WHERE  table_name = upper('&input_table_name')
new  11: WHERE  table_name = upper('ACC_POS_INT_TBL')
Enter value for input_owner: goex_admin
old  12:           AND owner = upper('&input_owner')
new  12:           AND owner = upper('goex_admin')

BLEV IDX_NAME                          LF_BLKS   DST_KEYS   NUM_ROWS LF_PER_KEY DAT_BLK_PER_KEY   CLUS_FCT LST_ANLY
---- ------------------------------ ---------- ---------- ---------- ---------- --------------- ---------- ---------
   2 I_ACC_POS_INT_TBL_BS_DT             93761        908   33659855        103             506     460007 30-SEP-11
   3 PK_ACC_POS_INT_TBL                 155658   33777720   33777720          1               1   33777447 27-SEP-11
   3 ACC_POS_INT_10DIG_IDX              160247   32850596   32850596          1               1   32763921 27-SEP-11

  建立索引后聚簇因子较小，差不多接近表上块的数量
  
  4.使用新创建索引后的执行计划   

Execution Plan
----------------------------------------------------------
Plan hash value: 2183566226

-------------------------------------------------------------------------------------------------------
| Id  | Operation                   | Name                    | Rows  | Bytes | Cost (%CPU)| Time     |
-------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT            |                         |  1065K|    39M| 17586   (1)| 00:03:32 |
|   1 |  FAST DUAL                  |                         |     1 |       |     2   (0)| 00:00:01 |
|   2 |  TABLE ACCESS BY INDEX ROWID| ACC_POS_INT_TBL         |  1065K|    39M| 17586   (1)| 00:03:32 |
|*  3 |   INDEX RANGE SCAN          | I_ACC_POS_INT_TBL_BS_DT |  1065K|       |  2984   (1)| 00:00:36 |
-------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   3 - access("BUSINESS_DATE">='20110701' AND "BUSINESS_DATE"<='20110728')

  从上面的执行计划看出，SQL语句已经选择了新建的索引
  尽管返回的rows,bytes没有明显的变化，但cost已经少了近7倍。